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Andreas Moshovos

Andreas Moshovos

D-Index & Metrics

Computer Science

D-Index
47
Citations
8876
World Ranking
6492
National Ranking
258

Research.com Recognitions

  • 2021 - IEEE Fellow For contributions to out-of-order processor microarchitecture and multiprocessor memory systems
  • 2017 - ACM Fellow For contributions to high-performance architecture including memory dependence prediction and snooping coherence
  • 2011 - ACM Senior Member

Overview

Andreas Moshovos is affiliated with the University of Toronto in Canada and primarily works in the field of Computer Science. Their research spans several subfields, including Artificial Intelligence, Computer Vision and Pattern Recognition, Hardware and Architecture, Molecular Biology, and Electrical and Electronic Engineering.

The main topics covered in Andreas Moshovos's research include Advanced Neural Network Applications, Parallel Computing and Optimization Techniques, CCD and CMOS Imaging Sensors, Advanced Optical Sensing Technologies, Stochastic Gradient Optimization Techniques, Topic Modeling, and Photoacoustic and Ultrasonic Imaging.

Their publication record features contributions to multiple venues, predominantly arXiv (Cornell University), as well as the IEEE Journal of Solid-State Circuits, the 2022 IEEE Symposium on VLSI Technology and Circuits, and AHFE International. Recent papers authored or coauthored by Andreas Moshovos include:

  • GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference, 2020, arXiv (Cornell University)
  • BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization, 2020, arXiv (Cornell University)
  • 39 000-Subexposures/s Dual-ADC CMOS Image Sensor With Dual-Tap Coded-Exposure Pixels for Single-Shot HDR and 3-D Computational Imaging, 2023, IEEE Journal of Solid-State Circuits
  • A 39,000 Subexposures/s CMOS Image Sensor with Dual-tap Coded-exposure Data-memory Pixel for Adaptive Single-shot Computational Imaging, 2022, 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)
  • Mokey: Enabling Narrow Fixed-Point Inference for Out-of-the-Box Floating-Point Transformer Models, 2022, arXiv (Cornell University)

Andreas Moshovos has collaborated frequently with several coauthors, including Ali Hadi Zadeh, Ameer Abdelhadi, Omar Mohamed Awad, Rahul Gulve, and Navid Sarhangnejad.

In recognition of their work, Andreas Moshovos has received several awards and honors. These include being named an IEEE Fellow in 2021 for contributions to out-of-order processor microarchitecture and multiprocessor memory systems, an ACM Fellow in 2017 for contributions to high-performance architecture including memory dependence prediction and snooping coherence, and an ACM Senior Member since 2011.

Best Publications

  • Cnvlutin: ineffectual-neuron-free deep neural network computing

    Jorge Albericio;Patrick Judd;Tayler Hetherington;Tor Aamodt

  • Demystifying GPU microarchitecture through microbenchmarking

    Henry Wong;Misel-Myrto Papadopoulou;Maryam Sadooghi-Alvandi;Andreas Moshovos

  • Dependence based prefetching for linked data structures

    Amir Roth;Andreas Moshovos;Gurindar S. Sohi

  • CHIMAERA: a high-performance architecture with a tightly-coupled reconfigurable functional unit

    Zhi Alex Ye;Andreas Moshovos;Scott Hauck;Prithviraj Banerjee

  • Dynamic speculation and synchronization of data dependences

    Andreas Moshovos;Scott E. Breach;T. N. Vijaykumar;Gurindar S. Sohi

  • Stripes: bit-serial deep neural network computing

    Patrick Judd;Jorge Albericio;Tayler Hetherington;Tor M. Aamodt

  • Spatial Memory Streaming

    Stephen Somogyi;Thomas F. Wenisch;Anastassia Ailamaki;Babak Falsafi

  • Low-leakage asymmetric-cell SRAM

    N. Azizi;F.N. Najm;A. Moshovos

  • JETTY: filtering snoops for reduced energy consumption in SMP servers

    A. Moshovos;G. Memik;B. Falsafi;A. Choudhary

  • Bit-pragmatic deep neural network computing

    Jorge Albericio;Alberto Delmas;Patrick Judd;Sayeh Sharify

  • RegionScout: Exploiting Coarse Grain Sharing in Snoop-Based Coherence

    Andreas Moshovos

  • Streamlining inter-operation memory communication via data dependence prediction

    Andreas Moshovos;Gurindar S. Sohi

  • A tagless coherence directory

    Jason Zebchuk;Moinuddin K. Qureshi;Vijayalakshmi Srinivasan;Andreas Moshovos

  • GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference

    Ali Hadi Zadeh;Isak Edo;Omar Mohamed Awad;Andreas Moshovos

  • Mechanisms for store-wait-free multiprocessors

    Thomas F. Wenisch;Anastasia Ailamaki;Babak Falsafi;Andreas Moshovos

  • Doppelgänger: a cache for approximate computing

    Joshua San Miguel;Jorge Albericio;Andreas Moshovos;Natalie Enright Jerger

  • Slice-processors: an implementation of operation-based prediction

    Andreas Moshovos;Dionisios N. Pnevmatikatos;Amirali Baniasadi

  • Accurate and complexity-effective spatial pattern prediction

    C.F. Chen;S.-H. Yang;B. Falsafi;A. Moshovos

  • Table based data speculation circuit for parallel processing computer

    Andreas I. Moshovos;Scott E. Breach;Terani N. Vijaykumar;Gurindar S. Sohi

  • Instruction distribution heuristics for quad-cluster, dynamically-scheduled, superscalar processors

    Amirali Baniasadi;Andreas Moshovos

  • Low-leakage asymmetric-cell SRAM

    Navid Azizi;Andreas Moshovos;Farid N. Najm

  • Stripes: Bit-Serial Deep Neural Network Computing

    Patrick Judd;Jorge Albericio;Andreas Moshovos

Frequent Co-Authors

Babak Falsafi
Babak Falsafi École Polytechnique Fédérale de Lausanne
Gurindar S. Sohi
Gurindar S. Sohi University of Wisconsin–Madison
Natalie Enright Jerger
Natalie Enright Jerger University of Toronto
Anastasia Ailamaki
Anastasia Ailamaki École Polytechnique Fédérale de Lausanne
Thomas F. Wenisch
Thomas F. Wenisch University of Michigan–Ann Arbor
Farid N. Najm
Farid N. Najm University of Toronto
Gennady Pekhimenko
Gennady Pekhimenko University of Toronto
Vijayalakshmi Srinivasan
Vijayalakshmi Srinivasan IBM (United States)
Raquel Urtasun
Raquel Urtasun University of Toronto
Scott Hauck
Scott Hauck University of Washington

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